Fuzzy Optimization and Decision Making

2019 ◽  
pp. 310-326 ◽  
Author(s):  
Dinesh C. S. Bisht ◽  
Pankaj Kumar Srivastava
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Fuzzy Optimization ◽  
Fuzzy Membership ◽  
Membership Functions ◽  
Recent Trends ◽  
Selection Of

Selection of the best out of several strategies is always a difficult task. Fuzzy criteria allow a better approach to deal with such situations. Fuzzy optimization is one of the best tools in decision making. This chapter covers the concept of fuzziness, fuzzy sets, fuzzy membership and the features of membership functions. Also is described is the classification of fuzzy optimization. Then, decision making and various models for decision making under fuzzy environments are discussed. Standard examples of fuzzy optimization-based decision-making are included to describe the recent trends. This chapter may help researchers to explore different aspects of fuzzy optimization in decision-making.

scholarly journals Fuzzy Optimization Model for post harvest selection process of Pecan (Carya illinoinensis)

2019 ◽  
Vol 8 (12S2) ◽  
pp. 421-425
Keyword(s):  
Fuzzy Logic ◽  
Selection Process ◽  
Fuzzy Optimization ◽  
Carya Illinoinensis ◽  
Membership Functions ◽  
Post Harvest ◽  
Quality Of Food ◽  
Selection Of

The quality of food is associated with a set of properties and characteristics that can be considered from its chemical and nutritional physical composition that have the ability to meet the needs of the consumer. The paper aims to evaluate the application of fuzzy logic in the evaluation and classification of the selection of pecans in the post harvest process using tests and instruments that determine their best quality. Fuzzy logic has proven to be very effective with matlab/simulink to develop and simulate the entire system, through an appropriate choice of rules and membership functions and applying the Mamdani method to defuzzification the results considering they are positive.

scholarly journals The n-Pythagorean Fuzzy Sets

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1772
Author(s):  
Anna Bryniarska
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Quadratic Function ◽  
Intuitionistic Fuzzy Sets ◽  
Membership Functions ◽  
Power Functions ◽  
Pythagorean Fuzzy Sets ◽  
Conceptual Apparatus ◽  
Intuitionistic Fuzzy ◽  
Classic Theory

The following paper presents deductive theories of n-Pythagorean fuzzy sets (n-PFS). N-PFS objects are a generalization of the intuitionistic fuzzy sets (IFSs) and the Yager Pythagorean fuzzy sets (PFSs). Until now, the values of membership and non-membership functions have been described on a one-to-one scale and a quadratic function scale. There is a symmetry between the values of this membership and non-membership functions. The scales of any power functions are used here in order to increase the scope of the decision-making problems. The theory of n-PFS introduces a conceptual apparatus analogous to the classic theory of Zadeh fuzzy sets, consistently striving to correctly define the n-PFS algebra.

scholarly journals Convexity and level sets for interval-valued fuzzy sets

2022 ◽  
Author(s):  
Pedro Huidobro ◽  
Pedro Alonso ◽  
Vladimír Janiš ◽  
Susana Montes
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Level Sets ◽  
Fuzzy Optimization ◽  
Interval Valued

AbstractConvexity is a deeply studied concept since it is very useful in many fields of mathematics, like optimization. When we deal with imprecision, the convexity is required as well and some important applications can be found fuzzy optimization, in particular convexity of fuzzy sets. In this paper we have extended the notion of convexity for interval-valued fuzzy sets in order to be able to cover some wider area of imprecision. We show some of its interesting properties, and study the preservation under the intersection and the cutworthy property. Finally, we applied convexity to decision-making problems.

scholarly journals A New Group Decision-Making Technique under Picture Fuzzy Soft Expert Information

Entropy ◽  
2021 ◽  
Vol 23 (9) ◽  
pp. 1176
Author(s):  
Fairouz Tchier ◽  
Ghous Ali ◽  
Muhammad Gulzar ◽  
Dragan Pamučar ◽  
Ganesh Ghorai
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Hybrid Model ◽  
Group Decision Making ◽  
Group Decision ◽  
Intuitionistic Fuzzy ◽  
Proposed Model ◽  
Picture Fuzzy Sets ◽  
Selection Of ◽  
Illustrative Application

As an extension of intuitionistic fuzzy sets, the theory of picture fuzzy sets not only deals with the degrees of rejection and acceptance but also considers the degree of refusal during a decision-making process; therefore, by incorporating this competency of picture fuzzy sets, the goal of this study is to propose a novel hybrid model called picture fuzzy soft expert sets by combining picture fuzzy sets with soft expert sets for dealing with uncertainties in different real-world group decision-making problems. The proposed hybrid model is a more generalized form of intuitionistic fuzzy soft expert sets. Some novel desirable properties of the proposed model, namely, subset, equality, complement, union and intersection, are investigated together with their corresponding examples. Two well-known operations AND and OR are also studied for the developed model. Further, a decision-making method supporting by an algorithmic format under the proposed approach is presented. Moreover, an illustrative application is provided for its better demonstration, which is subjected to the selection of a suitable company of virtual reality devices. Finally, a comparison of the initiated method is explored with some existing models, including intuitionistic fuzzy soft expert sets.

Analysis and Research of Direction Relation Based on Fuzzy Description

2011 ◽  
Vol 393-395 ◽  
pp. 1102-1105
Author(s):  
Yong Shan Liu ◽  
Yan Li
Keyword(s):  
Fuzzy Sets ◽  
Fuzzy Membership ◽  
Fuzzy Membership Function ◽  
Membership Degree ◽  
Membership Functions ◽  
Fuzzy Matrix ◽  
Fuzzy Membership Functions ◽  
Fuzzy Objects ◽  
Direction Relations ◽  
Fuzzy Description

A fuzzy membership function was defined for each direction to predict the membership degree that an object pertains to a certain direction. Nine fuzzy membership functions were defined to describe the direction relations between fuzzy objects and crisp objects with corresponding fuzzy sets. Direction relations were described by a 3×3 fuzzy matrix, which was computed by an aggregation operator defined on the nine fuzzy sets. The fuzzy matrices and crisp matrices of direction relations between fuzzy objects and crisp objects were computed respectively, and comparison of fuzzy matrices with crisp ones reveals that the proposed fuzzy approach is more effective than existing crisp method.

Feature selection by a distance measure method of subnormal and non-convex fuzzy sets

2021 ◽  
pp. 1-7
Author(s):  
Letao Qu ◽  
Bohyun Wang ◽  
Joon S. Lim
Keyword(s):  
Feature Selection ◽  
Fuzzy Sets ◽  
Distance Measure ◽  
Critical Role ◽  
Classification Systems ◽  
Fuzzy Rules ◽  
Fuzzy Classification ◽  
Fuzzy Membership ◽  
Membership Functions ◽  
Fuzzy Membership Functions

Distance measures of fuzzy sets have been developed for feature selection and finding redundant features in the fields of decision-making, prediction, and classification problems. Terms commonly used in the definition of fuzzy sets are normal and convex fuzzy sets. This paper extends the general fuzzy set definitions to subnormal and non-convex fuzzy sets that are more precise when implementing uncertain knowledge representations by weighing fuzzy membership functions. A distance measure method for subnormal and non-convex fuzzy sets is proposed for embedded feature selection. Constructing fuzzy membership functions and extracting fuzzy rules play a critical role in fuzzy classification systems. The weighted fuzzy membership functions prevent the combinatorial explosion of fuzzy rules in multiple fuzzy rule-based systems. The proposed method was validated by a comparison with two other methods. Our proposed method demonstrated higher accuracies in training and test, with scores of 97.95% and 93.98%, respectively, compared to the other two methods.

scholarly journals A Functional Approach to Audio Description

2020 ◽  
Vol 3 (2) ◽  
Author(s):  
Iwona Mazur
Keyword(s):  
Decision Making ◽  
Functional Model ◽  
Translation Studies ◽  
Functional Approach ◽  
Decision Making Process ◽  
Source Text ◽  
Audio Description ◽  
Text Types ◽  
Selection Of

The article discusses a functional approach to audio description (AD) and first proposes a classification of text types, followed by a model of source text (ST) analysis which encompasses three layers: the contextual, the macrotextual and the microtextual. The functional model helps identify the functional priorities in a given ST, which may then guide the audio describer’s decision-making process: the results of contextual and macrotextual analyses will assist the describer in the selection of the so-called macro strategy, while the microtextual analysis may help in making lower-level decisions called micro strategies. Although the model has been designed primarily for didactic purposes, its principles may also be useful for more experienced describers. Additionally, the model constitutes a theoretical conceptualisation of AD and attempts to better integrate AD within the field of translation studies.

Selection of an alternative based on interval-valued hesitant picture fuzzy sets

2021 ◽  
pp. 1-11
Author(s):  
Tabasam Rashid ◽  
M. Sarwar Sindhu
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Multiple Criteria Decision Making ◽  
Similarity Measures ◽  
Hesitant Fuzzy Sets ◽  
Ambiguous Information ◽  
Cosine Similarity Measures ◽  
Picture Fuzzy Sets ◽  
Interval Valued ◽  
Selection Of

Motivated by interval-valued hesitant fuzzy sets (IVHFSs) and picture fuzzy sets (PcFSs), a notion of interval-valued hesitant picture fuzzy sets (IVHPcFSs) is presented in this article. The concept of IVHPcFSs is put forward and some operational rules are developed to deal with it. The cosine similarity measures (SMs) are modified for IVHPcFSs to deal with interval-valued hesitant picture fuzzy (IVHPcF) data and the linear programming (LP) methodology is used to find out the criteria’s weights. A multiple criteria decision making (MCDM) approach is then developed to tackle the vague and ambiguous information involved in MCDM problems under the framework of IVHPcFSs. For the validation and strengthen of the proposed MCDM approach a practical example is put forward to select the educational expert at the end.

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